Mobile and Immersive Learning for Literacy in Emerging Economiesjfc/mattkam/... · 2008-03-16 · MILLEE: Mobile and Immersive Learning for Literacy in Emerging Economies Matthew

MILLEE:Mobile and Immersive Learning for Literacy in Mobile and Immersive Learning for Literacy in

Emerging Economies

Matthew KamDepartment of Electrical Engineering and Computer Sciences, and

B Dp g g p

Berkeley Institute of DesignUniversity of California, Berkeley

D i f D l

BERKELEY INSTITUTE OF DESIGNB DDesign for Development

UC San Diego, March 12, 2008

B DAcademic Background

Ph.D., Computer Science, UC Berkeley, 2008 (expected)

Prior degrees from UC Berkeley

• B.A., Economics

• B.S., Electrical Engineering & Computer Sciences

Coursework at UC Berkeley’s Graduate School of Education

• Literacy theory (2-semester sequence)

• Psychology of readingy gy g

• Second language acquisition

Diploma Teaching English as a Foreign Language 2008 (expected)Diploma, Teaching English as a Foreign Language, 2008 (expected)

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B DPrevious Projects

Location-Based Services for US immigrants• Goal: identify LBS applications for low-income • Goal: identify LBS applications for low-income,

Spanish-speaking agricultural workers

• Qualitative interviews with community volunteersQual tat ve te v ews w t co u ty volu tee s

U i l P b k Universal Passbooks (collaboration w/ Ricoh Innovations and Stanford Digital Vision Fellows program)

• Goal: identify social computing solutions for • Goal: identify social computing solutions for low-income US communities

• Qualitative interviews at homeless shelter and Qjob placement center

4Needs finding Systems design & implementation Evaluation


Livenotes [in ACM CHI 2005, ISLS CSCL 2002]

• Goal: recreate small-group learning g p gexperience in large lectures

• Developed multi-threaded application for h di i i i l l d T bl PCsynchronous discussions via wirelessly-connected Tablet PCs

Shared computer with multiple mice p p(collaboration w/ Microsoft Research India)

• Goal: split-screen game for collaborative learningcollaborative learning

• Mentored Master’s project by Andrea Moed & Owen Otto Andrea Moed & Owen Otto (James R. Chen award for outstanding Master’s project at Berkeley’s iSchool)



Microfinance in Uganda [in ACM CHI 2007a](collaboration w/ Hewlett-Packard consortium)

• Goal: field evaluation of handheld solution for tracking low-collateral loans

• International research fellowship from United Nations and UC Berkeley


B DDissertation Research

How can we harness “new media” to make literacy and language learning more accessible to literacy and language learning more accessible to low-income children in developing regions?

Some related projects:

One Laptop Per Child Shared computers with Same Language

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(Negroponte) multiple mice Subtitling (Kothari)(Microsoft-Berkeley)

B DHistorical Precedent

Sesame Street (Fisch and Truglio 2001)

Si 1968• Since 1968

• Combined education and entertainment

I t d hild i 120 t i• Impacted children in >120 countries

Streaming Sesame videos on cellphonesg p(Horowitz et al. 2006)

• Most benefits to households below or at poverty line

Explorations with Sesame-themed computer games, Internet-based games (Revelle et al. 2001)

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g• Lacked resources for summative learning assessments

B DEnglish in India

English is a global language: 1.2 to 1.5 billion people in >170 countries (Crystal 1997)people in >170 countries (Crystal 1997)

ESL is taught in almost all schools in India

Mastery of English is the “single most influential factor that determines access to … important avenues of economic and social advancement” (Kishwar 2005)

f d b d l h90% of indigenous web content in India is in English

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B D“World Language” Fluency

Low-income populations in Africa, Asia and Latin America desire to improve command of an pappropriate “world language” (Clegg, Ogange & Rodseth 2003; Faust & Nagar 2001; Kapadia 2005)

Widely spoken language, e.g. English, Mandarin, Spanish, etc.

Regional dialect is not necessarily native language for low-income groups

“World language” fluency opens the door to further education, “New Economy” jobs, higher incomes, social prestige etc

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social prestige, etc.

B DSchools Fail at “World Languages”

Schools in developing countries have limited impact

For example, in India:

• Rural ESL teachers communicated with us through ginterpreters

• 43% to 61% of school-going-age children do not g g gattend school regularly (Azim Premji Foundation 2004)

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B DOur Envisioned Solution

Mobile games that target learning anytime, anywhere

M k ESL l i ibl• Make ESL learning resources more accessible

Run on cellphonesRun on cellphones

• Fastest growing technology platform in developing world

B d • Battery powered

• Physically portable

Existing cellphone applications for literacy mostly leverage SMS

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literacy mostly leverage SMS

B DCase for E-Learning Games

Enhance motivation and learning (Jenkins 2005)

Incorporate good learning principles (Gee 2003)

P i d i d i t Prior randomized experiment (Banerjee et al. 2005)

• 2 years, >10,000 urban slums students in India

• Math-learning computer games twice per week

• Significant gains in math test scores

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B DProject Lifecycle (2004-08)

Human-centered design process• 7 rounds of field studies, totaling 7 months in Indiag

Summer 2004: needs assessment (rural + urban)Winter 2004: exploratory study (urban slums)p y y ( )Summer 2005: exploratory study (village school)

Summer 2006: feasibility study (urban slums)Summer 2006: feasibility study (urban slums)Winter 2006: feasibility study (village school)Summer 2007: further iterative design + testing

Winter 2007: commence longitudinal pilot

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B DExploratory Studies (2004-05)[in IEEE TEDC 2005, ACM IDC 2006, ACM CHI 2007a]

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B DDissertation Outline

Human-centered, fieldwork-based approach

Pedagogical design patterns

• Pimsleur Generator• Pimsleur Generator

• E-Learning games on cellphones

Traditional village games

F t di tiFuture directions

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B DPimsleur Audio CDs

Among most effective commercial products for conversational skills

• Based on Paul Pimsleur’s work (1967)

Targets functional contexts e g greetings travel• Targets functional contexts, e.g. greetings, travel

Supported by subsequent research on human pp y qmemory, retention and learning (Nation 2001)

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B DHow Pimsleur Works

Example from Hindi-learning unit

Learning principles

• Organic learning

• Anticipation

G d t d i t l ll• Graduated interval recall

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B DDrawbacks

Drawbacks with existing Pimsleur units

Prohibitive price• Prohibitive price

• Not localized for developing regions needs

Observations

L li ti t k l t t t l l • Localization can take place at content level, reuse pedagogical principles

• Pimsleur principles are repetitive can be expressed in • Pimsleur principles are repetitive, can be expressed in computational form

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B DPimsleur Generator

Authoring tool for generating custom Pimsleur-like audio units Text

fil

• Input: custom conversational script from local curriculum developer

MP3file

Pimsleur Generator

files

Audiofiles

(XML-based declarative language)

• Output: audio track which embodies Female: Hello.Male: Hello Ma’am.Female: Are you from India.

Metadata

planguage learning principles used in commercial Pimsleur units

Female: Are you from India.Male: Yes I’m from India.Male: Do you understand Hindi?Female: No, I don’t understand.

Oh you understand English.Male: Yes I understand English.

In future, can be extended to interactive version, e g conversational agent

Female: You understand very well.

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e.g. conversational agent

B DData Structures

Based on transcription of 4 Pimsleur units (30-min each)

• Devised uniform logic based on second language acquisition principles

Patterns for formulaic, oral language

• E g “This is a ”• E.g. This is a ___.

• Curriculum developer declares syntax tree to specify h l t tphrasal structure

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B DAlgorithms

• Organic learning teach (node) {if (node is a leaf) {

if (learner has not been taught meaning ofnode’s phrase) {

• Anticipation

• Graduated interval recall

say node’s meaning in native language;say node’s phrase in target language,

and asks learner to repeat aloud;pause;teach_pronunciation (node);anticipation (node);pinsert node into priority queue;

}}else {

if (learner has not been taught meaning ofphrase’s meaning or linguistic structurephrase s meaning or linguistic structure pertaining to node) {if (first child of node is a leaf)

say node’s meaning in native language;for each child of node {teach (child);graduated interval recall ();graduated_interval_recall ();

}if (learner has not encountered linguistic

structure pertaining to node & node hasexplanation for this structure)say node’s explanation in native language;

ti i ti ( d )

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anticipation (node);insert node into priority queue;

}}

}

B DBest-selling Foreign Language Packages

Avoid reinventing the wheel entirely

Reuse best practices from most successful commercial language learning packages

Reviewed sample of >35 applications

Sample has a balance b/w listening, reading speaking and writing skills

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B DDesign Pattern

“Template” solution to previous problemH b d i b l i d hit t • Have been used in urban planning and architecture (Alexander 1977), software engineering (Gamma et al. 1995), computer science education (Bergin) and games (Björk and Holopainen 2005)

Benefits Benefits • Represent solutions to frequent problems in skeletal form

Encourages reuse avoids reinventing the wheel• Encourages reuse, avoids reinventing the wheel

Distilled >50 patterns

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Distilled 50 patterns• Shortlisted 11 patterns for language beginners

B DPimsleur Generator: Results

Evaluated with 3 conversational scripts developed for grades 1 and 8 by India partners for grades 1 and 8 by India partners

• Declarative language for user input was sufficiently expressiveexpressive

Evaluated with 47 rural school children (grades 1-5) Evaluated with 47 rural school children (grades 1-5) over two weeks

N i h b l i• No post-test gains on short-term vocabulary retention

• Did not pay attention or respond to anticipation prompts

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B DE-Learning Games [in ACM CHI 2007b]

Designed and piloted 10 mobile games by applying pedagogical design patterns and game design principles (Crawford 2003, Malone 1981, Rouse 2001)

• Letter-sound correspondences

• Listening comprehension

• Word recognitiong

• Linguistic structures

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B DIterative Design and Testing [in ACM CHI 2007b, ACM DIS 2008, IEEE/ACM ICTD 2007]

Field-tested prototypes w/ three communities in North and South India• Urban slums school

• Private village school

• Government village schoolg

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B DResults: Learning Outcomes [in ACM DIS 2008]

First major quantitative study in summer 2007, with 47 rural school children (grades 2-5)(g )

Demonstrated short-term vocabulary retention1 96 out of 5 on pre test and • 1.96 out of 5 on pre-test, and

• 3.85 out of 5 on post-test(p-value < 0 001 std dev = 1 42)(p value < 0.001, std. dev. = 1.42)

B DResults: Gameplay Enjoyment [in ACM DIS 2008]

Players enjoyed showing off game achievements

• Winner screens

• Repeated over and over again

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B DCultural Relevance [in DiGRA 2007]

But most games fail to match the understanding or expectations that rural children have about gamesp g

• What are characteristics of traditional village games?

H d t diti l diff f id ?• How do traditional games differ from videogames?

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B DTraditional Village Games

Example: Tree-Tree

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B DToward a Design Grammar

Analyzed 28 traditional village games

S th i d k l i t d i Synthesized key rules into design grammar

Analogy to a design grammar• Nouns, e.g. entities and objects in the game world

• Adjectives, e.g. attributes of players and objectsj , g p y j

• Verbs, e.g. actions that change game state

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B DState Variables

Game state# f l t d i id• # of players, teams and opposing sides

• # of objects, e.g. ball, stone, stick, marble, pen

Player state• Position, i.e. x, y coordinates

• Active, at rest, imprisoned, invulnerable, out of game

Object stateObject state

• Position, i.e. x, y coordinates

Owner• Owner

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B DActions and Goals

Player actionsC t h d t t d t• Catch, evade, protect, guard, rescue, move, rest

Actions on objects• Throw, deflect, pick up, discard, strike, arrange, guess

Goals and end conditionsGoals and end conditions

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B DDifferences in Games

How are traditional Indian village games different from existing Western videogames?from existing Western videogames?

Compared design grammar against 296 game design patterns documented in Bj k d H l i 2005patterns documented in Bjork and Holopainen 2005

Identified absences or differences• Difficulty level based on subgoals

• Resource management

• Score-keeping

• No skill-acquisition for player characters

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• Lack of system-generated game events

• Rituals associated with physical space

B DApplying Grammar

Applied game design grammar

Tree-Tree Tree-Tree(playground version) (digital version)

R lt i t iti g d igResult: more intuitive game design

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B DOngoing Work

Longitudinal pilot deployment • From January 2008 to January 2009 (at the minimum)From January 2008 to January 2009 (at the minimum)

• Three times per week for rural children from poor families

• After-school program at private village school• After school program at private village school

Developing 1-year curriculum with experienced E li h t h i I diEnglish teacher in India

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B DTargeted Syllabus

Expected syllabus (both oral and written)

• Nouns related to: classroom items fruits & vegetables • Nouns related to: classroom items, fruits & vegetables, body parts, clothes, etc.

• Basic grammar: singular vs plural gender forms etc • Basic grammar: singular vs. plural, gender forms, etc.

• Question and answer: the 5 W’s and 1 H

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B DLatest Designs

Game design grammar, Sesame Street India characters

Gi i Ph dGiti Phod game

45Marbles game

B DHypothesized Results

Pre-tests, post-tests and delayed post-tests

Benchmark against standardized English exam

• 30 hours of instruction in English as a Second Language• 30 hours of instruction in English as a Second Language

Expect participants to learn more compared to h i l i l h ltheir lessons in government rural schools

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B DFuture Work (Summer 2008 and onwards)

Scenarios for informal learning

Other out of school settings e g home work play• Other out-of-school settings, e.g. home, work, play

Partnership w/ Sesame Workshop India

L ll d d f l l • Locally produced content for local learning needs

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Funded by recent grant from MacArthur Foundation (Digital Media and Learning award)

B DFuture Work (Summer 2008 and onwards)

Target Hispanic children and adults in migrant farming communitiesg

• Traditionally underserved by mainstream ESL commercial learning productslearning products

Funded by recent grant from Verizon

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B DAdult Language Learning

Goal: target lowly-educated adults in developing regions and industrialized countriesregions and industrialized countries

• Functional literacies for adults in service industries (e g call centers taxi drivers etc )industries (e.g. call centers, taxi drivers, etc.)

• Continuing education for female home-makers

Leverage convenience of mobile learning

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B DAcknowledgements

Thesis committee• Computer Science – Eric Brewer, John Canny• Education – Glynda Hull

Team members• Berkeley – Ruth Alexander, Jane Chiu, Varun Devanathan, Asya Grigorieva,

Dimas Guardado, Christopher Hom, Anjali Koppal, Maksim Lirov, Aaron McKee, David Nguyen, Anand Raghavan, Divya Ramachandran, Priyanka Reddy, Vij R d j M i h S bh l Ji t WVijay Rudraraju, Monish Subherwal, Jingtao Wang

• DA-IICT and IIT (India) – Aishvarya Agarwal, Anuj Kumar, Siddhartha Lal, Akhil Mathur, Anuj Tewari

Pilot team (India) M h Abidi A A d Siddh th Bh i • Pilot team (India) – Mehnaaz Abidi, Aman Anand, Siddharth Bhagwani, Jatin Chaudhary, Shirley Jain, Neelima Purwar, Gautam Singh, Kavish Sinha

Advocates

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Advocates• Jerome Feldman, Alastair Iles, Thomas Kalil, Annie Yeh

B DAcknowledgements

Collaborators in India• Sesame Workshop India – Sashwati Banerjeep j

• Suraksha - Rahul Chatterjee, Pratim Kumar, Shalini Mathur, Urvashi Sahni

• Mysore Literacy Trust - Babu Mathew, Soundara Rajan, M.L. Ramanarasimha

Funders• Big Ideas @ Berkeley - Serious Games competitiong @ y p

• Intel - Undergrad Research program

• MacArthur Foundation - Digital Media & Learning award

• Microsoft - Digital Inclusion award

• National Science Foundation - Grant No. 0326582

Q l

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• Qualcomm - Wireless Reach award

• Verizon

B DFor More Details

Matthew KamDepartment of Electrical Engineering and Computer Sciences, andp g g p ,Berkeley Institute of DesignUniversity of California, Berkeley, USAEmail: mattkam@cs berkeley eduEmail: [email protected]

Dissertation homepage: http://www.cs.berkeley.edu/~mattkam/millee

Dissertation work featured in TV documentary on novel cellphone applications in the developing worldCellphone: The Ring Heard Around the World.Produced by Canadian Broadcasting Corporation’s Documentary Production Unit, to be aired on public TV in Canada on April 3, 2008Viewable online after April 3: http://www.cbc.ca/documentaries

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Mobile and Immersive Learning for Literacy in Emerging Economiesjfc/mattkam/... · 2008-03-16 · MILLEE: Mobile and Immersive Learning for Literacy in Emerging Economies Matthew

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